AI-Driven Product Documentation Enhancement
AI-Driven Product Documentation Enhancement
CHALLENGE
Business context: Product team in financial services organisation received feedback that customers struggled to find information in user manuals and respond to regulatory inquiries as a consequence.
Problem statement: Lack of complete documentation created friction in customer experience and compliance reporting.
Strategic importance: Improved documentation directly impacts customer satisfaction, reduces support costs, and enhances regulatory compliance capabilities.
MY ROLE
Position and responsibilities: Innovation Product Manager leading experimental approach to validate documentation needs.
Team structure: Collaborated with technical team to design and implement AI-based solution.
APPROACH
Methodology: Applied design thinking combined with emerging AI technology to validate customer needs.
Key activities:
Formulated workshop to understand documentation requirements
Scoped technical experiment to evaluate potential solutions
Collaborated with technical team to repurpose large language model (LLM) for validation
Analysed user interaction patterns to identify priority documentation needs
Developed prototype of enhanced documentation approach
Stakeholder management: Aligned technical and product teams on experiment objectives and success criteria.
OUTCOME
Quantifiable results: Successfully validated customer need for supplemental documentation through data-driven approach.
Business impact: Identified opportunity to significantly improve customer experience and regulatory response capabilities.
Adoption/implementation: Findings led to creation of new documentation strategy with AI-assisted components.
LESSONS LEARNED
Personal growth: Developed expertise in applying AI technologies to solve practical business problems.
Key insights: Discovered that repurposing existing AI tools can provide cost-effective validation for product enhancements.
How this shaped future work: Created blueprint for using AI-driven approaches to validate customer needs before full-scale implementation.